In this study, a proposed process for the utilization of hydrogen sulphide separated with other gases from omani natural gas for the production of sulphuric acid by wet sulphuric acid process (WSA) was studied. The processwas simulated at an acid gas feed flow of 5000 m3/hr using Aspen ONE- V7.1-HYSYS software. A sensitivity analysis was conducted to determine the optimum conditions for the operation of plant. This included primarily the threepacked bed reactors connected in series for the production of sulphur trioxidewhich represented the bottleneck of the process. The optimum feed temperature and catalyst bed volume for each reactor were estimated and then used in the simulation of the whole process for two cases namely 4 and 6 mole% SO2 stream fed to the first catalytic reactor. The 4mole% SO2 gaves the highest conversion (98%) compared with 6 mole% SO2 (94.7%). A valuable quantity of heat was generated from the process. This excess heat could also be transformed into power in a turbine or used as a heating media in neighbouring process units.
In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the
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Under aerobic and anaerobic conditions, two laboratory-scale reactors were operated. Each reactor
was packed with 8.5 kg of shredded synthetic solid waste (less than 5 cm) that was prepared according to an
average composition of domestic solid waste in the city of Kirkuk. Using an air compressor, aerobic
conditions were created in the aerobic reactor. This study shows that the aerobic reactor was more efficient in
COD and BOD5 removal which were 97.88% and 91.25% while in case of anaerobic reactor, they were
66.53%and 19.11%, respectively.
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The extraction process of chlorophyll from dehydrated and pulverized alfalfa plant were studied by percolation method. Two solvent systems were used for the extraction namely; Ethanol-water and Hexane-Toluene systems . The effect of circulation rate, solvent concentration, and solvent volume to solid weight ratio were studied. In both ethanol water, and Hexane-Toluene systems it appears that solvent concentration is the most effective variable.
Linguistic taboos exist in most cultures. Tabooed words are generally being culturespecific
and relating to bodily functions or aspects of a culture that are sacred. Such words are
avoided, considered inappropriate and loaded with affective meaning and failing to adhere to.
Strict rules, often, governing their use and lead to punishment or public shame. These taboo
words can be used as a way of violating social deixis represented by four types of honorifics;
addressee, referent, bystander, and finally setting honorifics. This paper shows how these
taboo words are used in Kenneth Bernard's play La Justice or The Cock that Crew from the
theatre of the Ridiculous as means of violating social deixis in its four types. Th
ABSTRACT
The study aims to identify the level of health services provided in private suites to government hospitals from the perspective of the recipi
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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It is very difficult to obtain the value of a rock strength along the wellbore. The value of Rock strength utilizing to perform different analysis, for example, preventing failure of the wellbore, deciding a completion design and, control the production of sand. In this study, utilizing sonic log data from (Bu-50) and (BU-47) wells at Buzurgan oil field. Five formations have been studied (Mishrif, Sadia, Middle lower Kirkuk, Upper Kirkuk, and Jaddala) Firstly, calculated unconfined compressive strength (UCS) for each formation, using a sonic log method. Then, the derived confined compressive rock strengthens from (UCS) by entering the effect of bore and hydrostatic pressure for each formation. Evaluations th
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This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
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